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Record W2150875240 · doi:10.5539/ijef.v3n1p124

Intrinsic Bubbles in the American Stock Exchange: The case of the S&P 500 Index

2011· article· en· W2150875240 on OpenAlexvenueno aff
Kamel Naoui

Bibliographic record

VenueInternational Journal of Economics and Finance · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
FundersRaymond and Beverly Sackler Institute for Biological, Physical and Engineering Sciences, Yale UniversityYale University
KeywordsCointegrationEconomicsDividendEconometricsIndex (typography)BubbleSeries (stratigraphy)Stock priceStock (firearms)Sample (material)Financial economicsThermodynamicsPhysicsComputer scienceMechanicsFinanceMaterials scienceGeology

Abstract

fetched live from OpenAlex

The aim of this paper is to test the presence of rational intrinsic bubbles in the S&P 500 index. To this effect, we used two econometric techniques. The first technique applies stationarity and cointegration tests to real prices and dividends series. The second technique consists in directly estimating intrinsic bubbles coefficients. Studying a sample of annual real price and dividends indices, observed during the 1871 to 2009 period, we note the presence of a bubble with features consistent with intrinsic bubbles theory.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.239
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2011
Admission routes1
Has abstractyes

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